Crandore Hub

FuzzyImputationTest

Imputation Procedures and Quality Tests for Fuzzy Data

Special procedures for the imputation of missing fuzzy numbers are still underdeveloped. The goal of the package is to provide the new d-imputation method (DIMP for short, Romaniuk, M. and Grzegorzewski, P. (2023) "Fuzzy Data Imputation with DIMP and FGAIN" RB/23/2023) and covert some classical ones applied in R packages ('missForest','miceRanger','knn') for use with fuzzy datasets. Additionally, specially tailored benchmarking tests are provided to check and compare these imputation procedures with fuzzy datasets.

Versions across snapshots

VersionRepositoryFileSize
0.5.2 rolling source/ R- FuzzyImputationTest_0.5.2.tar.gz 51.2 KiB
0.5.2 rolling linux/jammy R-4.5 FuzzyImputationTest_0.5.2.tar.gz 137.6 KiB
0.5.2 latest source/ R- FuzzyImputationTest_0.5.2.tar.gz 51.2 KiB
0.5.2 latest linux/jammy R-4.5 FuzzyImputationTest_0.5.2.tar.gz 137.6 KiB
0.5.2 2026-04-23 source/ R- FuzzyImputationTest_0.5.2.tar.gz 51.2 KiB
0.5.2 2026-04-09 windows/windows R-4.5 FuzzyImputationTest_0.5.2.zip 140.8 KiB
0.5.0 2025-04-20 source/ R- FuzzyImputationTest_0.5.0.tar.gz 50.9 KiB

Dependencies (latest)

Imports

Suggests